Specialist, Data Engineer (Pyhton, SQL, Databricks, AI/LLM/Agentic AI)

Build, develop, and operate scalable production-grade data pipelines and AI-ready data products supporting Gartner's quantitative research capabilities.

Partner with cross-functional teams (Product, Data Science, Economic Modelling, Research) to productionize data and AI capabilities at scale.

Implement and improve data quality frameworks, production data platforms, and establish data standards to ensure trusted, decision-grade data for analytics and research.

Master's degree in Computer Science, Data Science, Statistics, Software Engineering, Information Systems, or related quantitative discipline.

0-2 years of professional experience in data engineering, data management, analytics, or software engineering involving data integration and quality.

Strong programming skills in Python and experience with SQL and modern data engineering technologies (e.g., ETL/ELT tools, APIs, cloud or AI-enabled platforms like Databricks).

Understanding of software engineering best practices (testing, code quality, version control), data quality, governance, and scalable engineering practices.

Early career data engineer comfortable working at the intersection of data engineering, analytics, AI, and research in a fast-paced, high-growth environment.

Proficient in translating complex business and technical problems into scalable data and analytical solutions with a focus on production-grade deployment.

Collaborative operator who can partner with technical and non-technical stakeholders to contextualize and communicate data insights for impact on research and decision-making.